Chapter 1 Exercise 6
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Chapter 1 Exercise 6:
Yes, there could be a potential for confounding factor because of age groups. A person that is in their twenties has a different health problem then someone that is in their forties. Another problem potential could be dependent on whom the actual subjects are, it can be male or female, infants or children, to adults or elderly. These could all be potential confounding factors.
Chapter 1 Exercise 13:
To figure out the most dangerous and least dangerous jobs, we need to first figure out what the rate of death is. To figure out the rate, I took total death divided by total employed. The numbers tells me that the Fishers and fishing workers has the highest rate which means the most dangerous jobs. While the Construction laborers have the lowest rate which implies that its the least dangerous jobs. What the numbers dont tell us is that, a construction worker knowing that they are working in a very dangerous environment will be extra careful than a fishing worker. There could be potential confounding factors that we do not know using just numbers.
Occupation
Total Deaths
Total Employed
Rate=total death/total employed
Drivers
3,412,370
0.00029100
Farmers
829,680
0.00041100
Construction
1,493,390
0.00022700
Miscellaneous agr Workers
758,620
0.00023200
Aircraft pilots
121,070
0.00066903
logging
86,110
0.00092904
fishers
40,540
0.00118402
electrical power
110,090
0.00032701
structural iron
62,940
0.00055609
refuse and recyclable
73,050
0.00043806
Chapter 1 Exercise 15:
This study is an experimental one since there is a control group and a treatment group.
A confounding factor here could be age group again. A teenager will say an answer without weighing in the options while an adult will have more life/work experiences that they have already gone through to say answers. Another confounding factor could be experiences and knowledge, again a younger person hasnt had a lot of life experiences or have enough knowledge on the subject while an adult in their forties will have more experiences and knowledge to answer the questions correctly.
Another confounding factor could be genders, as males and females could be a variable in the answers given. Males tend to be more knowledge in sports and thus are more likely to answer them correctly while females tend to less knowledge in sports and are more likely to answer them incorrectly.
If I were to redesign this experiment, I would first divide the people by gender, then make half the males “treatment” group and the other “control” group. I would do the same for the females which will create a even distribution of males and females. I would also ask the same types of questions to both genders and both groups to ensure there are no gaps in knowledge. Another distinction that I would make here is to also factor in age group, as younger adults are more athletic than the older folks. Thus the “control” group will have young and old males and females and the “treatment” group will have the same. This will eliminate as much confounding factors as we can.
Chapter 2 Exercise 33:
TMKR showed the most price variability at 206.748 while BTX stock has the highest average price at 309.7. Per my excel attached, to calculate the average price of each stock, I typed “=average(B2:B32)” in cell B33, then drag the formula across the right to capture all the other stocks. I do the same thing with Standard Deviation except instead of typing “=average”, I tpyed “=STDEVP). To calculate Variability, typed “=B33/B34” in cell B35 and dragged B35 across once again.